1. Field
The present disclosure relates to a driver state sensing system, a driver state sensing method, and a vehicle including the same, and more particularly to a driver state sensing system, a driver state sensing method, and a vehicle including the same for estimating change of a driver's gaze or head to determine whether the driver is in a drowsiness state, and to perform a warning according to the driver's drowsiness.
2. Description of the Related Art
Today, many people are injured every year due to accidents caused by drowsiness driving. In particular, when a driver of a large vehicle such as a bus or a truck drives drowsiness driving, a driver of another vehicle and even an occupant of the large vehicle may suffer damage.
Accordingly, in order to reduce traffic accidents caused by an explosive increase in the number of vehicles, a lot of efforts are being made in the development of Advanced Safety Vehicle (ASV). Technological developments in the ASV include drowsiness driving alarm systems, nighttime obstacle detection systems, vehicle hazard alarm systems and the like.
Of these, the drowsiness driving alarm systems alert a driver after detecting the drowsiness driving based on the image analysis for the driver's state such as the flicker of eyes through the CCD camera, that is, the driver's behavior, thereby obstructing drowsiness driving so that stable driving can be performed.
However, the conventional drowsiness driving alarm systems tried to recognize a driver's sleepiness or carelessness by using the biological signals such as detecting the blinking of a driver's pupil or measuring a driver's heart rate and brain wave. However, recognizing the pupil is affected by the internal illuminance of the vehicle, the brightness of the surrounding environment, the lighting condition, and the external weather. In addition, there is a problem in that it is difficult to cope with the case where the driver is wearing glasses or it is hard to recognize the pupil, such as sunglasses and the like. Accordingly, a method for detecting a driver's motion by using a stereo camera has been developed, but this method has problems that the cost incurred due to the additional mounting of the image sensor for the stereo camera configuration is increased, and a large amount of computation is consumed in the extraction of a 3D image using a stereo image, which makes real-time image processing difficult.
In addition, there is a problem that sensing the status of a driver by recognizing a biological signal is costly due to mounting the bio-signal detection device on a vehicle.